SummaryMost hereditary diseases in humans are genetically complex, resulting from combinations of mutations in multiple genes. However synthetic interactions between genes are very difficult to identify in population studies because of a lack of statistical power and we fundamentally do not understand how mutations interact to produce phenotypes. C. elegans is a unique animal in which genetic interactions can be rapidly identified in vivo using RNA interference, and we recently used this system to construct the first genetic interaction network for any animal, focused on signal transduction genes. The first objective of this proposal is to extend this work and map a comprehensive genetic interaction network for this model metazoan. This project will provide the first insights into the global properties of animal genetic interaction networks, and a comprehensive view of the functional relationships between genes in an animal. The second objective of the proposal is to use C. elegans to develop and validate experimentally integrated gene networks that connect genes to phenotypes and predict genetic interactions on a genome-wide scale. The methods that we develop and validate in C. elegans will then be applied to predict phenotypes and interactions for human genes. The final objective is to dissect the molecular mechanisms underlying genetic interactions, and to understand how these interactions evolve. The combined aim of these three objectives is to generate a framework for understanding and predicting how mutations interact to produce phenotypes, including in human disease.

Most hereditary diseases in humans are genetically complex, resulting from combinations of mutations in multiple genes. However synthetic interactions between genes are very difficult to identify in population studies because of a lack of statistical power and we fundamentally do not understand how mutations interact to produce phenotypes. C. elegans is a unique animal in which genetic interactions can be rapidly identified in vivo using RNA interference, and we recently used this system to construct the first genetic interaction network for any animal, focused on signal transduction genes. The first objective of this proposal is to extend this work and map a comprehensive genetic interaction network for this model metazoan. This project will provide the first insights into the global properties of animal genetic interaction networks, and a comprehensive view of the functional relationships between genes in an animal. The second objective of the proposal is to use C. elegans to develop and validate experimentally integrated gene networks that connect genes to phenotypes and predict genetic interactions on a genome-wide scale. The methods that we develop and validate in C. elegans will then be applied to predict phenotypes and interactions for human genes. The final objective is to dissect the molecular mechanisms underlying genetic interactions, and to understand how these interactions evolve. The combined aim of these three objectives is to generate a framework for understanding and predicting how mutations interact to produce phenotypes, including in human disease.

SummaryAdvanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.

Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.

Max ERC Funding

1 000 000 €

Duration

Start date: 2010-04-01, End date: 2015-03-31

Project acronymAN07AT

ProjectUnderstanding computational roles of new neurons generated in the adult hippocampus

SummaryNew neurons are continuously generated in certain regions of adult mammalian brain. One of those regions is the dentate gyrus, a subregion of hippocampus, which is essential for memory formation. Although these new neurons in the adult dentate gyrus are thought to have an important role in learning and memory, it is largely unclear how new neurons are involved in information processing and storage underlying memory. Because new neurons constitute a minor portion of intermingled local neuronal population, simple application of conventional techniques such as multi-unit extracellular recording and pharmacological lesion are not suitable for the functional analysis of new neurons. In this proposed research program, I will combine multi-unit recording and behavioral analysis with virus mediated, cell-type-specific genetic manipulation of neuronal activity, to investigate computational roles of new neurons in learning and memory. Specifically, I will determine: 1) specific memory processes that require new neurons, 2) dynamic patterns of activity that new neurons express during memory-related behavior, 3) influence of new neurons on their downstream structure. Further, based on the information obtained by these three lines of studies, we will establish causal relationship between specific memory-related behavior and specific pattern of activity in new neurons. Solving these issues will cooperatively provide important insight into the understanding of computational roles performed by adult neurogenesis. The information on the function of new neurons in normal brain could contribute to future development of efficient therapeutic strategy for a variety of brain disorders.

New neurons are continuously generated in certain regions of adult mammalian brain. One of those regions is the dentate gyrus, a subregion of hippocampus, which is essential for memory formation. Although these new neurons in the adult dentate gyrus are thought to have an important role in learning and memory, it is largely unclear how new neurons are involved in information processing and storage underlying memory. Because new neurons constitute a minor portion of intermingled local neuronal population, simple application of conventional techniques such as multi-unit extracellular recording and pharmacological lesion are not suitable for the functional analysis of new neurons. In this proposed research program, I will combine multi-unit recording and behavioral analysis with virus mediated, cell-type-specific genetic manipulation of neuronal activity, to investigate computational roles of new neurons in learning and memory. Specifically, I will determine: 1) specific memory processes that require new neurons, 2) dynamic patterns of activity that new neurons express during memory-related behavior, 3) influence of new neurons on their downstream structure. Further, based on the information obtained by these three lines of studies, we will establish causal relationship between specific memory-related behavior and specific pattern of activity in new neurons. Solving these issues will cooperatively provide important insight into the understanding of computational roles performed by adult neurogenesis. The information on the function of new neurons in normal brain could contribute to future development of efficient therapeutic strategy for a variety of brain disorders.

SummaryMost of the lymphomas diagnosed in the western world are originated from mature B cells. The hallmark of these malignancies is the presence of recurrent chromosome translocations that usually involve the immunoglobulin loci and a proto-oncogene. As a result of the translocation event the proto-oncogene becomes deregulated under the influence of immunoglobulin cis sequences thus playing an important role in the etiology of the disease. Upon antigen encounter mature B cells engage in the germinal center reaction, a complex differentiation program of critical importance to the development of the secondary immune response. The germinal center reaction entails the somatic remodelling of immunoglobulin genes by the somatic hypermutation and class switch recombination reactions, both of which are triggered by Activation Induced Deaminase (AID). We have previously shown that AID also initiates lymphoma-associated c-myc/IgH chromosome translocations. In addition, the germinal center reaction involves a fine-tuned balance between intense B cell proliferation and program cell death. This environment seems to render B cells particularly vulnerable to malignant transformation. We aim at studying the molecular events responsible for B cell susceptibility to lymphomagenesis from two perspectives. First, we will address the role of AID in the generation of lymphomagenic lesions in the context of AID specificity and transcriptional activation. Second, we will approach the regulatory function of microRNAs of AID-dependent, germinal center events. The proposal aims at the molecular understanding of a process that lies in the interface of immune regulation and oncogenic transformation and therefore the results will have profound implications both to basic and clinical understanding of lymphomagenesis.

Most of the lymphomas diagnosed in the western world are originated from mature B cells. The hallmark of these malignancies is the presence of recurrent chromosome translocations that usually involve the immunoglobulin loci and a proto-oncogene. As a result of the translocation event the proto-oncogene becomes deregulated under the influence of immunoglobulin cis sequences thus playing an important role in the etiology of the disease. Upon antigen encounter mature B cells engage in the germinal center reaction, a complex differentiation program of critical importance to the development of the secondary immune response. The germinal center reaction entails the somatic remodelling of immunoglobulin genes by the somatic hypermutation and class switch recombination reactions, both of which are triggered by Activation Induced Deaminase (AID). We have previously shown that AID also initiates lymphoma-associated c-myc/IgH chromosome translocations. In addition, the germinal center reaction involves a fine-tuned balance between intense B cell proliferation and program cell death. This environment seems to render B cells particularly vulnerable to malignant transformation. We aim at studying the molecular events responsible for B cell susceptibility to lymphomagenesis from two perspectives. First, we will address the role of AID in the generation of lymphomagenic lesions in the context of AID specificity and transcriptional activation. Second, we will approach the regulatory function of microRNAs of AID-dependent, germinal center events. The proposal aims at the molecular understanding of a process that lies in the interface of immune regulation and oncogenic transformation and therefore the results will have profound implications both to basic and clinical understanding of lymphomagenesis.

Max ERC Funding

1 596 000 €

Duration

Start date: 2008-12-01, End date: 2014-11-30

Project acronymBIDECASEOX

ProjectBio-inspired Design of Catalysts for Selective Oxidations of C-H and C=C Bonds

Researcher (PI)Miguel Costas Salgueiro

Host Institution (HI)UNIVERSITAT DE GIRONA

Call DetailsStarting Grant (StG), PE5, ERC-2009-StG

SummaryThe selective functionalization of C-H and C=C bonds remains a formidable unsolved problem, owing to their inert nature. Novel alkane and alkene oxidation reactions exhibiting good and/or unprecedented selectivities will have a big impact on bulk and fine chemistry by opening novel methodologies that will allow removal of protection-deprotection sequences, thus streamlining synthetic strategies. These goals are targeted in this project via design of iron and manganese catalysts inspired by structural elements of the active site of non-heme enzymes of the Rieske Dioxygenase family. Selectivity is pursued via rational design of catalysts that will exploit substrate recognition-exclusion phenomena, and control over proton and electron affinity of the active species. Moreover, these catalysts will employ H2O2 as oxidant, and will operate under mild conditions (pressure and temperature). The fundamental mechanistic aspects of the catalytic reactions, and the species implicated in C-H and C=C oxidation events will also be studied with the aim of building on the necessary knowledge to design future generations of catalysts, and provide models to understand the chemistry taking place in non-heme iron and manganese-dependent oxygenases.

The selective functionalization of C-H and C=C bonds remains a formidable unsolved problem, owing to their inert nature. Novel alkane and alkene oxidation reactions exhibiting good and/or unprecedented selectivities will have a big impact on bulk and fine chemistry by opening novel methodologies that will allow removal of protection-deprotection sequences, thus streamlining synthetic strategies. These goals are targeted in this project via design of iron and manganese catalysts inspired by structural elements of the active site of non-heme enzymes of the Rieske Dioxygenase family. Selectivity is pursued via rational design of catalysts that will exploit substrate recognition-exclusion phenomena, and control over proton and electron affinity of the active species. Moreover, these catalysts will employ H2O2 as oxidant, and will operate under mild conditions (pressure and temperature). The fundamental mechanistic aspects of the catalytic reactions, and the species implicated in C-H and C=C oxidation events will also be studied with the aim of building on the necessary knowledge to design future generations of catalysts, and provide models to understand the chemistry taking place in non-heme iron and manganese-dependent oxygenases.

SummaryIncreases in nutrient availability and temperature, and changes in precipitation patterns and biodiversity are important components of global environmental change. Thus, it is imperative to understand their impacts on the functioning of natural ecosystems. Substantial research efforts are being currently devoted to predict how biodiversity will respond to global change. However, little is known on the relative importance of biodiversity against other attributes of biotic communities, such as species cover and spatial pattern, as a driver of ecosystem processes. Furthermore, the effects of global change on the relationships between these attributes and ecosystem functioning are virtually unknown. This project aims to evaluate the relationships between community attributes (species richness, composition, evenness, cover, and spatial pattern) and key processes related to ecosystem functioning under different global change scenarios. Its specific objectives are to: i) evaluate the relative importance of community attributes as drivers of ecosystem functioning, ii) assess how multiple global change drivers will affect key ecosystem processes, iii) test whether global change drivers modify observed community attributes-ecosystem functioning relationships, iv) develop models to forecast global change effects on ecosystem functioning, and v) set up protocols for the establishment of mitigation actions based on the results obtained. They will be achieved by integrating experimental and modeling approaches conducted with multiple biotic communities at different spatial scales. Such integrated framework has not been tackled before, and constitutes a ground breaking advance over current research efforts on global change. This proposal will also open the door to new research lines exploring the functional role of community attributes and their importance as modulators of ecosystem responses to global change.

Increases in nutrient availability and temperature, and changes in precipitation patterns and biodiversity are important components of global environmental change. Thus, it is imperative to understand their impacts on the functioning of natural ecosystems. Substantial research efforts are being currently devoted to predict how biodiversity will respond to global change. However, little is known on the relative importance of biodiversity against other attributes of biotic communities, such as species cover and spatial pattern, as a driver of ecosystem processes. Furthermore, the effects of global change on the relationships between these attributes and ecosystem functioning are virtually unknown. This project aims to evaluate the relationships between community attributes (species richness, composition, evenness, cover, and spatial pattern) and key processes related to ecosystem functioning under different global change scenarios. Its specific objectives are to: i) evaluate the relative importance of community attributes as drivers of ecosystem functioning, ii) assess how multiple global change drivers will affect key ecosystem processes, iii) test whether global change drivers modify observed community attributes-ecosystem functioning relationships, iv) develop models to forecast global change effects on ecosystem functioning, and v) set up protocols for the establishment of mitigation actions based on the results obtained. They will be achieved by integrating experimental and modeling approaches conducted with multiple biotic communities at different spatial scales. Such integrated framework has not been tackled before, and constitutes a ground breaking advance over current research efforts on global change. This proposal will also open the door to new research lines exploring the functional role of community attributes and their importance as modulators of ecosystem responses to global change.

SummaryThe search of singularities in incompressible flows has become a major challenge in the area of non-linear partial differential equations and is relevant in applied mathematics, physics and engineering. The existence of such singularities would have important consequences for the understanding of turbulence. One way to make progress in this direction, is to study plausible scenarios for the singularities supported by experiments or numerical analysis. With the more sophisticated numerical tools now available, the subject has recently gained considerable momentum. The main goal of this project is to study analytically several incompressible fluid models. In particular solutions that involve the possible formation of singularities or quasi-singular structures.

The search of singularities in incompressible flows has become a major challenge in the area of non-linear partial differential equations and is relevant in applied mathematics, physics and engineering. The existence of such singularities would have important consequences for the understanding of turbulence. One way to make progress in this direction, is to study plausible scenarios for the singularities supported by experiments or numerical analysis. With the more sophisticated numerical tools now available, the subject has recently gained considerable momentum. The main goal of this project is to study analytically several incompressible fluid models. In particular solutions that involve the possible formation of singularities or quasi-singular structures.

SummaryWith the availability of the essentially complete sequence of the human genome, as well as a rapid development of massive sequencing techniques, the research efforts to understand genetics and disease from a cis standpoint will soon reach an endpoint. However, our emerging knowledge of gene regulation networks reveals that epigenetic regulation of the hereditary information plays crucial roles in various biological events through its influence on processes such as transcription, DNA replication and chromosome architecture. Another scenario in which the control of chromatin structure is crucial is the repair of lesions in genomic DNA. There is mounting evidence, particularly from model organisms such as Saccharomyces cerevisiae, that histone modifying enzymes (acetylases, deacetylases, kinases, …) are essential components of the machinery that maintains genome integrity and thereby guards against cancer, degenerative diseases and ageing. However, little is known about the specific “code” of histone tail modifications that coordinate DNA repair, and the impact that an aberrant “histone code” may have on human health. In CHROMOREPAIR we will systematically analyze the chromatin remodelling process that undergoes at DNA lesions and evaluate the impact that chromatin alterations have on the access, signaling and repair of DNA damage. Furthermore, we propose to translate our in vitro knowledge to the development of mouse models that help us evaluate how modulation of chromatin status impinges on genome maintenance and therefore on cancer and aging. As a provocative line of research and based on our preliminary data, we propose that certain chromatin alterations could not only impair but also in some cases promote a more robust response to DNA breaks, which could be a novel and not yet explored way to potentiate the elimination of pre-cancerous cells.

With the availability of the essentially complete sequence of the human genome, as well as a rapid development of massive sequencing techniques, the research efforts to understand genetics and disease from a cis standpoint will soon reach an endpoint. However, our emerging knowledge of gene regulation networks reveals that epigenetic regulation of the hereditary information plays crucial roles in various biological events through its influence on processes such as transcription, DNA replication and chromosome architecture. Another scenario in which the control of chromatin structure is crucial is the repair of lesions in genomic DNA. There is mounting evidence, particularly from model organisms such as Saccharomyces cerevisiae, that histone modifying enzymes (acetylases, deacetylases, kinases, …) are essential components of the machinery that maintains genome integrity and thereby guards against cancer, degenerative diseases and ageing. However, little is known about the specific “code” of histone tail modifications that coordinate DNA repair, and the impact that an aberrant “histone code” may have on human health. In CHROMOREPAIR we will systematically analyze the chromatin remodelling process that undergoes at DNA lesions and evaluate the impact that chromatin alterations have on the access, signaling and repair of DNA damage. Furthermore, we propose to translate our in vitro knowledge to the development of mouse models that help us evaluate how modulation of chromatin status impinges on genome maintenance and therefore on cancer and aging. As a provocative line of research and based on our preliminary data, we propose that certain chromatin alterations could not only impair but also in some cases promote a more robust response to DNA breaks, which could be a novel and not yet explored way to potentiate the elimination of pre-cancerous cells.

Max ERC Funding

948 426 €

Duration

Start date: 2008-12-01, End date: 2013-11-30

Project acronymCRC PROGRAMME

ProjectDissecting the roles of the beta-catenin and Tcf genetic programmes during colorectal cancer progression

SummaryMost colorectal cancers (CRCs) are initiated by activating mutations in components of the Wnt signalling pathway. Physiological Wnt signals are required for the specification and maintenance of the stem and progenitor cell compartments of the intestinal crypts. We demonstrated that early colorectal lesions exhibit a constitutive Wnt target gene programme, which is very similar to that of normal intestinal stem and progenitor cells. We originally proposed that colorectal adenomas behave as clusters of intestinal cells locked into a constitutive crypt progenitor phenotype. Given the prevalence of Wnt signalling mutations in CRC, an outstanding endeavour is the characterization of the similarities and differences in the instructions dictated by beta-catenin and Tcf to normal intestinal cells vs. CRC cells. Here, we propose to systematically compare and catalogue the beta-catenin/Tcf genetic programmes in intestinal progenitor/stem cells, intestinal adenomas and late CRCs. Transcriptomic analysis of isolated normal progenitor cells and tumor cell populations combined with bioinformatic analysis of gene regulatory networks will allow us to workout the hierarchical interactions downstream of beta-catenin and Tcf. Moreover, functional analysis of key beta-catenin/Tcf target genes using genetically modified mice models will help us to pinpoint which Wnt-controlled functions are essential for tumor maintenance and progression in vivo. Moreover, we seek to understand the tumor suppressor role of EphB2 and EphB3 receptors, two beta-catenin/Tcf target genes in normal crypts and benign colorectal adenomas, that block cancer progression by compartmentalizing tumor cells at the onset of CRC. Overall, our results will shed light on the relationship between stem/progenitor cells and cancer and hold potential for the future development of both therapeutic and diagnostic tools.

Most colorectal cancers (CRCs) are initiated by activating mutations in components of the Wnt signalling pathway. Physiological Wnt signals are required for the specification and maintenance of the stem and progenitor cell compartments of the intestinal crypts. We demonstrated that early colorectal lesions exhibit a constitutive Wnt target gene programme, which is very similar to that of normal intestinal stem and progenitor cells. We originally proposed that colorectal adenomas behave as clusters of intestinal cells locked into a constitutive crypt progenitor phenotype. Given the prevalence of Wnt signalling mutations in CRC, an outstanding endeavour is the characterization of the similarities and differences in the instructions dictated by beta-catenin and Tcf to normal intestinal cells vs. CRC cells. Here, we propose to systematically compare and catalogue the beta-catenin/Tcf genetic programmes in intestinal progenitor/stem cells, intestinal adenomas and late CRCs. Transcriptomic analysis of isolated normal progenitor cells and tumor cell populations combined with bioinformatic analysis of gene regulatory networks will allow us to workout the hierarchical interactions downstream of beta-catenin and Tcf. Moreover, functional analysis of key beta-catenin/Tcf target genes using genetically modified mice models will help us to pinpoint which Wnt-controlled functions are essential for tumor maintenance and progression in vivo. Moreover, we seek to understand the tumor suppressor role of EphB2 and EphB3 receptors, two beta-catenin/Tcf target genes in normal crypts and benign colorectal adenomas, that block cancer progression by compartmentalizing tumor cells at the onset of CRC. Overall, our results will shed light on the relationship between stem/progenitor cells and cancer and hold potential for the future development of both therapeutic and diagnostic tools.

SummaryDSGE models are the standard tool of quantitative macroeconomics. We use them to measure economics phenomena and to provide policy advice. However, since Kydland and Prescott s 1982, the profession has fought about how to take these models to the data. Kydland and Prescott proposed to calibrate their model. Why? Macroeconomists could not compute their models efficiently. Moreover, the techniques required for estimating DSGE models using the likelihood did not exist. Finally, models were ranked very badly by likelihood ratio tests. Calibration offered a temporary solution. By focusing only on a very limited set of moments of the model, researchers could claim partial success and keep developing their theory. The landscape changed in the 1990s. There were developments along three fronts. First, macroeconomists learned how to efficiently compute equilibrium models with rich dynamics. Second, statisticians developed simulation techniques like Markov chain Monte Carlo (MCMC), which we require to estimate DSGE models. Third, and perhaps most important, computer power has become so cheap that we can now do things that were unthinkable 20 years ago. This proposal tries to estimate non-linear and/or non-normal DSGE models using a likelihood approach. Why non-linear models? Previous research has proved that second order approximation errors in the policy function have first order effects on the likelihood function. Why non-normal models? Time-varying volatility is key to understanding the Great Moderation. Kim and Nelson (1999), McConnell and Pérez-Quirós (2000), and Stock and Watson (2002) have documented a decline in the variance of output growth since the mid 1980s. Only DSGE models with richer structure than normal innovations can account for this.

DSGE models are the standard tool of quantitative macroeconomics. We use them to measure economics phenomena and to provide policy advice. However, since Kydland and Prescott s 1982, the profession has fought about how to take these models to the data. Kydland and Prescott proposed to calibrate their model. Why? Macroeconomists could not compute their models efficiently. Moreover, the techniques required for estimating DSGE models using the likelihood did not exist. Finally, models were ranked very badly by likelihood ratio tests. Calibration offered a temporary solution. By focusing only on a very limited set of moments of the model, researchers could claim partial success and keep developing their theory. The landscape changed in the 1990s. There were developments along three fronts. First, macroeconomists learned how to efficiently compute equilibrium models with rich dynamics. Second, statisticians developed simulation techniques like Markov chain Monte Carlo (MCMC), which we require to estimate DSGE models. Third, and perhaps most important, computer power has become so cheap that we can now do things that were unthinkable 20 years ago. This proposal tries to estimate non-linear and/or non-normal DSGE models using a likelihood approach. Why non-linear models? Previous research has proved that second order approximation errors in the policy function have first order effects on the likelihood function. Why non-normal models? Time-varying volatility is key to understanding the Great Moderation. Kim and Nelson (1999), McConnell and Pérez-Quirós (2000), and Stock and Watson (2002) have documented a decline in the variance of output growth since the mid 1980s. Only DSGE models with richer structure than normal innovations can account for this.